Parameter estimation of nonlinear chaotic system by improved TLBO strategy

Estimation of parameters of chaotic systems is a subject of substantial and well-developed research issue in nonlinear science. From the viewpoint of optimization, parameter estimation can be formulated as a multi-modal constrained optimization problem with multiple decision variables. This investig...

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Vydané v:	Soft computing (Berlin, Germany) Ročník 20; číslo 12; s. 4965 - 4980
Hlavní autori:	Zhang, Hongjun, Li, Baozhu, Zhang, Jun, Qin, Yuanhui, Feng, Xiaoyi, Liu, Bo
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2016 Springer Nature B.V
Predmet:	Artificial Intelligence Biogeography Chaos theory Computational Intelligence Control Engineering Evolutionary algorithms Genetic algorithms Heuristic methods Learning Lorenz system Mathematical Logic and Foundations Mechatronics Methodologies and Application Methods Optimization Parameter estimation Parameter identification Particle swarm optimization Robotics Students Teaching Time series Memetic algorithm Parameter estimation System identification Chaotic system Nelder–Mead simplex algorithm Teaching–learning-based optimization
ISSN:	1432-7643, 1433-7479
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